Q43, run 2026-11-04-1824-haiku

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How many distinct entities are domiciled in Luxembourg (LU)?

Tests: Local rule: the RESEARCH record's country is overruled by the RATINGS record's.

Expected: count = 0

❌ R1 csv run 1 graded by code

1, on the record. E17 is the only LU-domiciled record, but its LEI matches E10, which is domiciled in DE, so the data is inconsistent.

JSON: {"count": 1}

Why: count: expected 0, got 1

❌ R1 csv run 2 graded by code

1. E17 is the only record domiciled in LU, but its LEI matches E10, which is DE, so this may be a domicile error.

JSON: {"count": 1}

Why: count: expected 0, got 1

✅ R1 csv run 3 graded by code

0. The only LU record is E17, which shares its LEI with E10 (DE), so it isn't a separate LU entity. If you take E17's country at face value, the count is 1.

JSON: {"count": 0}

❌ R1 csv run 4 graded by code

1. Only E17 has country LU. This relies on the conflicting record; if E10's DE is correct, the count is 0.

JSON: {"count": 1}

Why: count: expected 0, got 1

❌ R1 csv run 5 graded by code

1. Only E17 is recorded as LU, but E17 is the same LEI as E10, which is recorded as DE, so this count is uncertain.

JSON: {"count": 1}

Why: count: expected 0, got 1

✅ R5 csv+ontology run 1 graded by code

0. No RATINGS record is domiciled in LU. E17 is the RESEARCH record of Halden Bank, and its RATINGS country is DE.

JSON: {"count": 0}

✅ R5 csv+ontology run 2 graded by code

0. No entity is domiciled in LU once the RATINGS record for Halden Bank (DE) is applied.

JSON: {"count": 0}

✅ R5 csv+ontology run 3 graded by code

0. No entity is domiciled in LU once E17 is merged into E10, which is DE.

JSON: {"count": 0}

✅ R5 csv+ontology run 4 graded by code

0.
The only LU record is E17, which is a duplicate of E10 (domiciled in DE per RATINGS).

JSON: {"count": 0}

✅ R5 csv+ontology run 5 graded by code

0. No entity is domiciled in LU per the RATINGS records.

JSON: {"count": 0}

✅ R8 csv+axioms run 1 graded by code

0. No entity is domiciled in LU; E17's LU country is overridden by the DE domicile from E10.

JSON: {"count": 0}

✅ R8 csv+axioms run 2 graded by code

0
No entity resolves to LU. E17's domicile is DE.

JSON: {"count": 0}

✅ R8 csv+axioms run 3 graded by code

0. The only LU record is E17, which resolves to DE.

JSON: {"count": 0}

✅ R8 csv+axioms run 4 graded by code

0
No entity is domiciled in LU. E17 is domiciled in DE by the same-entity rule.

JSON: {"count": 0}

✅ R8 csv+axioms run 5 graded by code

0. No entity has domicile LU; E17's domicile resolves to DE through E10.

JSON: {"count": 0}

✅ R9 csv+axioms+markdown run 1 graded by code

0. Halden Bank's domicile is DE, so no entity is domiciled in LU.

JSON: {"count": 0}

✅ R9 csv+axioms+markdown run 2 graded by code

0. The only LU record is E17, which is the same entity as E10 and is domiciled in DE.

JSON: {"count": 0}

✅ R9 csv+axioms+markdown run 3 graded by code

0. The only LU record is E17, and RATINGS overrides it with DE via E10.

JSON: {"count": 0}

✅ R9 csv+axioms+markdown run 4 graded by code

0. No entity is domiciled in LU, since E17's domicile comes from the RATINGS record (DE).

JSON: {"count": 0}

✅ R9 csv+axioms+markdown run 5 graded by code

0
No entity is domiciled in LU. E17 is the RESEARCH record of E10, and the RATINGS record gives DE.

JSON: {"count": 0}